响应面模型与混合优化算法相结合的锯片参数优化设计

发布时间：2018-03-28 21:29

本文选题：锯片　切入点：响应面模型　出处：《中国机械工程》2016年22期

【摘要】：针对传统算法在锯片声学特征优化中的局限性,提出了一种将二阶响应面模型与混合算法相结合的优化设计方法。在设计区域内应用D-optimal试验设计法抽取样本点,分别通过显式算法获取锯片声学、应力响应以及隐式算法获取锯片变形量,并用试验验证了数值模型的准确性,然后建立了由6个变量参数所决定的锯片的声学、应力以及刚度的二阶响应面模型;利用自适应模拟退火法和蛙跳混合算法对响应面模型进行循环逼近,获得了设计变量影响度以及最优结果。结果表明,在保证刚度和应力许可条件下,通过有限次数值分析,经全局优化后的最佳结构可降低空载噪声4~7dB。数字算例表明,该方法适用于旋转类刀具的声学性能优化设计。
[Abstract]:In view of the limitation of the traditional algorithm in the optimization of saw blade acoustic characteristics, an optimal design method combining the second-order response surface model with the hybrid algorithm is proposed. The D-optimal experimental design method is used to extract the sample points in the design area. The acoustics of saw blade, stress response and implicit algorithm are obtained by explicit algorithm, respectively. The accuracy of numerical model is verified by experiments, and the acoustics of saw blade determined by six variable parameters are established. The second order response surface model of stress and stiffness is approximated by the adaptive simulated annealing method and the hybrid algorithm of leapfrog. The influence degree of design variables and the optimal results are obtained. Under the condition that stiffness and stress are guaranteed, the optimal structure after global optimization can reduce the no-load noise by 4 ~ 7 dB through finite numerical analysis. The numerical example shows that this method is suitable for the optimal design of acoustic performance of rotary cutters.
【作者单位】：河北工业大学;
【基金】：天津市自然科学基金重点资助项目(11JCZDJC23100) 河北省自然科学基金资助项目(F2014202241)
【分类号】：TG717

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